A portable electronic device, such as mobile phones, tablets, laptops or media players, includes a user interface that can use systems like speech recognition for initiating a process or performing a task without providing tactile inputs. However, the conventionally used speech recognition system cannot be used very frequently as it consumes more power and memory to perform core functions such as turning ON/OFF the device, changing modes of the device, reading emails etc., thus resulting in high computational cost, and thus high energy consumption which is prohibitive in a portable device
Existing prior art solutions provide technologies for controlling such portable devices through speech recognition systems. One such system is disclosed in a US Patent Application number US20150106085A1 that provides a system for parallel speech recognition processing of multiple audio signals produced by multiple microphones in a handheld portable electronic device. A primary processor transitions to a power-saving mode while an auxiliary processor remains active. The auxiliary processor then monitors the speech of a user of the device to detect a wake-up command by speech recognition processing the audio signals in parallel. When the auxiliary processor detects the command, it then signals the primary processor to transition to active mode. The auxiliary processor may also identify to the primary processor which microphone resulted in the command being recognized with the highest confidence.
Another U.S. Pat. No. 9,020,870B1 disclosing a recall system using spiking neuron networks to identify an unknown external stimulus is provided. The recall system includes one or more processors and a memory, with the memory storing computer code which, when executed by the one or more processors, cause the one or more processors to perform the operations described herein. For example, the system receives a first input signal (having spatial-temporal data) originating from a known external stimulus. The spatial-temporal data is converted into a first spike train. The first spike train is received in a spiking neuron network that generates a first set of polychronous groups (PCGs) as a result of the first spike train.
Another U.S. Pat. No. 6,081,782A provides a voice command control and verification system and method to store for each authorized user, one or a series of speech models of voice commands or phrases uttered by the authorized user. Each speech model has an associated action component which specifies the specific action that the authorized user desires in response to the issuance of the corresponding voice command. User's identity is verified; thereafter a voice command is generated. Voice command is matched. If there is a match, claimed identity and voice command corresponding to it are verified. Upon successful verification, the command is executed in accordance with the associated action component.
Further, the portable devices such as mobile phones or tablets have multiple inbuilt microphones in order to improve quality of audio signals provided to the speech recognition system. For an instance, if a user is speaking in crowded area, it would be difficult to separate acoustic signal from the background noise, or it would be difficult to detect accurate word or sentence. So, the issues like understanding of syntax and semantics may occur while providing speech signal in real time. Furthermore, for the conventional speech recognition system, at least part of the speech recognition system may be running all the time and it also requires significant digital signal processing to select the “best” microphones to use and then generate the signal. Thus, it may result in too much power consumption and time delay.
In order to solve the aforementioned problems of high power consumption, time delay, high computational cost and the like, a neuromorphic system for controlling a wireless device by means of voice commands processed by an artificial neural network is provided.